Prioritizing the Components of Online Environment to Assess Customer Experience: An Interpretive Structural Modeling Approach

R. Garg, Vandana, Vinod Kumar
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Abstract

The present study aims to identify and prioritize the components of customer experience in online environment. The study employs Pareto analysis and interpretive structural modeling (ISM) to accomplish above-mentioned objective. Firstly, 36 components have been derived from extensively reviewed literature, and out of them, 15 were finalized as vital few variables having 80% influence in creating customer experience in online environment. To assess the impact of these 15 components, one outcome component ‘Customer Experience (Flow)' has been added. So, an ISM technique is applied on a total of 16 components of customer experience in online environment. The aim of this technique is to highlight the interrelationships among the components and to prioritize them. Further, the findings are strengthened by using MICMAC analysis. Results revealed that time distortion, skill, focused attention, interactivity, playfulness, start web, and involvement are found to have weak dependence powers but with strong driving powers. However, control, challenge, arousal, telepresence, flow, positive affect, and exploratory behavior were found to possess weak driving power and strong dependence power. The results of the present study carry implications for academicians and marketers handling online experience of their customers.
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在线环境组件的优先级评估客户体验:一种解释结构建模方法
本研究旨在识别并优先考虑在线环境中客户体验的组成部分。本研究采用帕累托分析和解释结构模型(ISM)来实现上述目标。首先,从广泛审查的文献中得出36个组成部分,其中15个被最终确定为对在线环境中创建客户体验具有80%影响的重要少数变量。为了评估这15个组件的影响,增加了一个结果组件“客户体验(流程)”。因此,将ISM技术应用于在线环境中客户体验的16个组成部分。该技术的目的是突出组件之间的相互关系,并对它们进行优先排序。此外,使用MICMAC分析加强了研究结果。结果发现,时间扭曲、技能、注意力集中、互动性、游戏性、启动网络和参与性的依赖能力较弱,而驱动能力较强。控制行为、挑战行为、唤醒行为、临场表现行为、心流行为、积极情感行为和探索行为的驱动能力较弱,依赖能力较强。本研究的结果对学者和营销人员处理其客户的在线体验具有启示意义。
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